Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "94" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 52 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 50 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2459867 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.698902 | -1.077320 | -1.131716 | -0.722965 | 0.952098 | 1.639389 | 2.735952 | 3.184768 | 0.6982 | 0.6791 | 0.4111 | nan | nan |
| 2459866 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.636775 | -1.362867 | -0.925788 | -1.000826 | 1.473605 | 2.222056 | 1.783555 | 2.905074 | 0.7023 | 0.6831 | 0.4007 | nan | nan |
| 2459865 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.116162 | -0.555316 | 8.958335 | 8.523613 | 0.452393 | 2.501455 | 3.148919 | 2.329760 | 0.7242 | 0.7018 | 0.3598 | nan | nan |
| 2459864 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.701365 | -0.395601 | 0.305761 | 0.293232 | 0.371555 | 1.473589 | 5.958297 | 10.158974 | 0.6925 | 0.6670 | 0.4201 | nan | nan |
| 2459863 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -1.155032 | -1.207891 | 0.229977 | 0.515564 | 1.611184 | 2.171198 | 4.696492 | 5.690686 | 0.6905 | 0.6608 | 0.4072 | nan | nan |
| 2459862 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.902390 | -0.519929 | -0.659013 | 0.089548 | -0.370107 | 3.500066 | 0.955508 | 2.218616 | 0.6773 | 0.6921 | 0.4194 | nan | nan |
| 2459861 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.812291 | -0.451699 | 0.205225 | 0.611222 | 0.436863 | 1.504717 | 1.810107 | 5.457173 | 0.7051 | 0.6729 | 0.4187 | nan | nan |
| 2459860 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.643186 | -1.301658 | -0.384446 | 0.021836 | 0.092172 | 2.495788 | 2.780238 | 2.797174 | 0.7099 | 0.6741 | 0.4178 | nan | nan |
| 2459859 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.932500 | -1.005784 | 0.354822 | 0.696462 | 1.323805 | 1.489988 | 2.982073 | 1.857738 | 0.7160 | 0.6782 | 0.4130 | nan | nan |
| 2459858 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.812607 | -1.348273 | 0.085758 | 0.614650 | 1.363026 | 1.857272 | 4.691926 | 5.651535 | 0.7280 | 0.6841 | 0.4245 | 3.168297 | 2.562517 |
| 2459857 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 0.008865 | -0.512795 | 0.451975 | -0.043500 | 0.669376 | 10.306886 | 2.624802 | 6.691515 | 0.0246 | 0.0247 | 0.0004 | nan | nan |
| 2459856 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 3.43% | 0.57% | -1.147957 | -1.028670 | -0.313479 | 0.122431 | 0.191958 | 1.292467 | 1.737927 | 2.315492 | 0.7190 | 0.6998 | 0.4072 | 1.602470 | 1.399195 |
| 2459855 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 75.333640 | 75.362434 | inf | inf | 4363.440967 | 4363.275470 | 4164.583632 | 4163.430438 | 0.0101 | 0.0089 | 0.0015 | 0.000000 | 0.000000 |
| 2459854 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -1.193211 | -0.977563 | -0.646744 | -0.484966 | 1.442229 | 1.610791 | 2.422423 | 6.533055 | 0.7226 | 0.7398 | 0.4397 | 3.031626 | 2.486903 |
| 2459853 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.296624 | -1.729511 | -0.467066 | -0.576897 | 0.368822 | 1.823597 | 2.542937 | 6.273088 | 0.7419 | 0.6873 | 0.4314 | 3.439177 | 2.919377 |
| 2459852 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 8.65% | 0.00% | -0.680963 | -1.208406 | 0.473251 | -0.951121 | 1.116798 | 1.432498 | -0.001208 | -0.440267 | 0.8317 | 0.8380 | 0.2444 | 2.690442 | 2.510824 |
| 2459851 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.299052 | -0.799333 | 0.255967 | 0.660195 | 0.810642 | 4.883736 | 2.692665 | 5.568707 | 0.7616 | 0.7400 | 0.3462 | 4.136749 | 3.050132 |
| 2459850 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.487723 | -1.234243 | -0.286644 | 0.761658 | 0.712114 | 2.763637 | 2.899059 | 6.527852 | 0.7462 | 0.7531 | 0.3589 | 3.521399 | 2.953408 |
| 2459849 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.380960 | 0.630859 | 0.226418 | 2.317872 | 0.728519 | 1.600933 | 5.109285 | 5.667750 | 0.7404 | 0.7402 | 0.3598 | 4.128892 | 3.207339 |
| 2459848 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 30.15% | 0.00% | -1.516718 | -0.424208 | -0.633843 | 0.105210 | -0.123642 | 3.088966 | 2.304237 | 0.746073 | 0.7213 | 0.7460 | 0.3813 | 1.380106 | 1.308336 |
| 2459847 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.997426 | -1.553724 | -0.827547 | -0.133346 | 0.236094 | 2.740126 | 4.809473 | 4.692335 | 0.7266 | 0.6817 | 0.4369 | 3.623646 | 2.917579 |
| 2459845 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -1.079024 | -1.201600 | 0.477540 | 0.244585 | 0.670400 | 3.086600 | 6.269844 | 3.547003 | 0.7530 | 0.7509 | 0.3655 | 0.000000 | 0.000000 |
| 2459844 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 0.993116 | -0.300735 | 0.677697 | -0.683030 | 11.840318 | 13.007496 | 8.795177 | 6.399509 | 0.0244 | 0.0242 | 0.0005 | nan | nan |
| 2459843 | digital_ok | 100.00% | 0.66% | 0.66% | 0.00% | 100.00% | 0.00% | -1.211817 | -1.978948 | -0.251460 | -1.111313 | 0.100692 | 1.046387 | 7.245663 | 2.041501 | 0.7508 | 0.7491 | 0.3911 | 5.733802 | 5.227246 |
| 2459842 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.218594 | -0.954424 | 0.521978 | 0.715350 | -0.193695 | 0.750584 | 2.019539 | 0.111372 | 0.7617 | 0.6754 | 0.2674 | 1.707312 | 1.600332 |
| 2459841 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 1.844937 | 0.288589 | 0.840234 | -0.864946 | 23.838755 | 8.944076 | 5.546136 | 2.492797 | 0.0244 | 0.0242 | 0.0005 | nan | nan |
| 2459840 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 2.929791 | 0.126945 | 0.704404 | -0.782771 | 5.112549 | 0.001445 | 2.384589 | 0.739032 | 0.0229 | 0.0229 | 0.0005 | nan | nan |
| 2459839 | digital_ok | 0.00% | - | - | - | - | - | 0.186532 | -0.901992 | 1.845432 | -1.341459 | 0.083477 | -0.784096 | 2.739029 | -0.463581 | nan | nan | nan | nan | nan |
| 2459838 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 194.552087 | 195.864048 | inf | inf | 12151.467839 | 12103.343041 | 8206.817675 | 8160.083377 | nan | nan | nan | 0.000000 | 0.000000 |
| 2459836 | digital_ok | - | 100.00% | 100.00% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.0365 | 0.0484 | 0.0027 | nan | nan |
| 2459835 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459833 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | -1.034425 | -1.079333 | 1.016286 | -0.216529 | 0.458243 | 31.707681 | 2.491097 | 10.604562 | 0.0282 | 0.0312 | 0.0016 | nan | nan |
| 2459832 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.858645 | -2.482219 | -1.112090 | -0.579565 | 0.975822 | 2.711670 | 1.641482 | 8.940240 | 0.7433 | 0.4340 | 0.5731 | 3.453655 | 2.903284 |
| 2459831 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | 0.027675 | -0.949881 | 1.443644 | -1.138712 | 2.306900 | 0.513733 | 3.478663 | -0.081432 | 0.0294 | 0.0327 | 0.0019 | nan | nan |
| 2459830 | digital_ok | 100.00% | 0.00% | 16.13% | 0.00% | 100.00% | 0.00% | -1.440522 | -1.525487 | -0.869157 | -1.138520 | -0.591093 | 6.976892 | 3.870383 | 10.286625 | 0.7360 | 0.4231 | 0.5580 | 4.379318 | 3.846687 |
| 2459829 | digital_ok | 100.00% | 0.00% | 1.61% | 0.00% | 100.00% | 0.00% | -2.043486 | -1.021965 | 0.060251 | -0.396546 | 0.012244 | 1.808906 | 5.855955 | 13.544735 | 0.6607 | 0.5570 | 0.4187 | 12.210351 | 8.188964 |
| 2459828 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -0.486147 | -1.414414 | 0.030110 | 0.095460 | -0.717554 | 3.153513 | 3.772003 | 1.383776 | 0.7293 | 0.4334 | 0.5365 | 1.983420 | 1.653411 |
| 2459827 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -1.185920 | -1.835654 | -0.457376 | -0.462858 | -0.093478 | 1.377368 | 5.398538 | 3.911519 | 0.6740 | 0.5712 | 0.4218 | 6.974581 | 5.184767 |
| 2459826 | digital_ok | 100.00% | 16.13% | 16.13% | 0.00% | 100.00% | 0.00% | -1.014022 | -1.297624 | -0.727914 | -0.945261 | -0.660514 | 3.629647 | 3.400309 | 10.484137 | 0.6569 | 0.4107 | 0.4625 | 8.806617 | 9.109334 |
| 2459825 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.735770 | -1.421956 | -0.682362 | -0.666619 | 0.464054 | 3.059760 | 2.228934 | 2.411647 | 0.0772 | 0.1025 | 0.0175 | 0.000000 | 0.000000 |
| 2459824 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.245006 | -1.463384 | -0.720938 | -0.957327 | 2.041318 | 3.593913 | 5.105871 | 5.165810 | 0.0705 | 0.0888 | 0.0079 | 0.000000 | 0.000000 |
| 2459823 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.967149 | -1.697189 | -0.696849 | -1.002644 | -0.765968 | 6.328372 | 7.235540 | 13.993654 | 0.0745 | 0.0896 | 0.0132 | 0.000000 | 0.000000 |
| 2459822 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.947257 | -1.554103 | -0.290975 | 0.106237 | -0.137241 | 1.557493 | 4.916300 | 2.098078 | 0.0801 | 0.0955 | 0.0162 | 0.000000 | 0.000000 |
| 2459821 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.901646 | -2.077737 | -0.063161 | -0.331214 | 0.219371 | 2.303752 | 2.202750 | 3.636340 | 0.0761 | 0.0824 | 0.0138 | 1.243352 | 1.226651 |
| 2459820 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -1.353949 | -1.659899 | 0.019094 | -0.771066 | 1.053488 | 2.979745 | 5.655166 | 7.871715 | 0.0692 | 0.0921 | 0.0096 | 0.000000 | 0.000000 |
| 2459817 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 0.064489 | -0.373467 | -0.078779 | -0.703689 | -0.762008 | 1.172883 | 1.209582 | 4.368111 | 0.0878 | 0.0914 | 0.0138 | 15.035802 | 14.940087 |
| 2459816 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.440170 | -0.739282 | -0.621665 | -1.204784 | -0.407642 | 3.449304 | 6.009291 | 8.233591 | 0.0729 | 0.0886 | 0.0209 | 23.977953 | 20.318179 |
| 2459815 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.236784 | -0.206881 | -0.647617 | -1.052641 | -0.517516 | 2.021268 | 4.128146 | 8.468923 | 0.0876 | 0.0946 | 0.0137 | 0.000000 | 0.000000 |
| 2459814 | digital_ok | 0.00% | - | - | - | - | - | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459813 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -1.187967 | -2.629263 | -0.303594 | -0.710578 | 2.079480 | 3.891385 | 2.975274 | 7.443236 | 0.0904 | 0.1297 | 0.0219 | 0.000000 | 0.000000 |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 3.184768 | -0.698902 | -1.077320 | -1.131716 | -0.722965 | 0.952098 | 1.639389 | 2.735952 | 3.184768 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 2.905074 | -1.362867 | -0.636775 | -1.000826 | -0.925788 | 2.222056 | 1.473605 | 2.905074 | 1.783555 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | ee Power | 8.958335 | -0.116162 | -0.555316 | 8.958335 | 8.523613 | 0.452393 | 2.501455 | 3.148919 | 2.329760 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 10.158974 | -0.395601 | -0.701365 | 0.293232 | 0.305761 | 1.473589 | 0.371555 | 10.158974 | 5.958297 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 5.690686 | -1.155032 | -1.207891 | 0.229977 | 0.515564 | 1.611184 | 2.171198 | 4.696492 | 5.690686 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Variability | 3.500066 | -0.902390 | -0.519929 | -0.659013 | 0.089548 | -0.370107 | 3.500066 | 0.955508 | 2.218616 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 5.457173 | -0.451699 | -0.812291 | 0.611222 | 0.205225 | 1.504717 | 0.436863 | 5.457173 | 1.810107 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 2.797174 | -0.643186 | -1.301658 | -0.384446 | 0.021836 | 0.092172 | 2.495788 | 2.780238 | 2.797174 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | ee Temporal Discontinuties | 2.982073 | -0.932500 | -1.005784 | 0.354822 | 0.696462 | 1.323805 | 1.489988 | 2.982073 | 1.857738 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 5.651535 | -1.348273 | -0.812607 | 0.614650 | 0.085758 | 1.857272 | 1.363026 | 5.651535 | 4.691926 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Variability | 10.306886 | -0.512795 | 0.008865 | -0.043500 | 0.451975 | 10.306886 | 0.669376 | 6.691515 | 2.624802 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 2.315492 | -1.147957 | -1.028670 | -0.313479 | 0.122431 | 0.191958 | 1.292467 | 1.737927 | 2.315492 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Power | inf | 75.362434 | 75.333640 | inf | inf | 4363.275470 | 4363.440967 | 4163.430438 | 4164.583632 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 6.533055 | -0.977563 | -1.193211 | -0.484966 | -0.646744 | 1.610791 | 1.442229 | 6.533055 | 2.422423 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 6.273088 | -1.729511 | -0.296624 | -0.576897 | -0.467066 | 1.823597 | 0.368822 | 6.273088 | 2.542937 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Variability | 1.432498 | -0.680963 | -1.208406 | 0.473251 | -0.951121 | 1.116798 | 1.432498 | -0.001208 | -0.440267 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 5.568707 | -0.299052 | -0.799333 | 0.255967 | 0.660195 | 0.810642 | 4.883736 | 2.692665 | 5.568707 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 6.527852 | -0.487723 | -1.234243 | -0.286644 | 0.761658 | 0.712114 | 2.763637 | 2.899059 | 6.527852 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 5.667750 | -0.380960 | 0.630859 | 0.226418 | 2.317872 | 0.728519 | 1.600933 | 5.109285 | 5.667750 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Variability | 3.088966 | -0.424208 | -1.516718 | 0.105210 | -0.633843 | 3.088966 | -0.123642 | 0.746073 | 2.304237 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | ee Temporal Discontinuties | 4.809473 | -1.553724 | -0.997426 | -0.133346 | -0.827547 | 2.740126 | 0.236094 | 4.692335 | 4.809473 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | ee Temporal Discontinuties | 6.269844 | -1.201600 | -1.079024 | 0.244585 | 0.477540 | 3.086600 | 0.670400 | 3.547003 | 6.269844 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Variability | 13.007496 | 0.993116 | -0.300735 | 0.677697 | -0.683030 | 11.840318 | 13.007496 | 8.795177 | 6.399509 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | ee Temporal Discontinuties | 7.245663 | -1.978948 | -1.211817 | -1.111313 | -0.251460 | 1.046387 | 0.100692 | 2.041501 | 7.245663 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | ee Temporal Discontinuties | 2.019539 | 0.218594 | -0.954424 | 0.521978 | 0.715350 | -0.193695 | 0.750584 | 2.019539 | 0.111372 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | ee Temporal Variability | 23.838755 | 1.844937 | 0.288589 | 0.840234 | -0.864946 | 23.838755 | 8.944076 | 5.546136 | 2.492797 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | ee Temporal Variability | 5.112549 | 2.929791 | 0.126945 | 0.704404 | -0.782771 | 5.112549 | 0.001445 | 2.384589 | 0.739032 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | ee Temporal Discontinuties | 2.739029 | -0.901992 | 0.186532 | -1.341459 | 1.845432 | -0.784096 | 0.083477 | -0.463581 | 2.739029 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Power | inf | 195.864048 | 194.552087 | inf | inf | 12103.343041 | 12151.467839 | 8160.083377 | 8206.817675 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Variability | 31.707681 | -1.079333 | -1.034425 | -0.216529 | 1.016286 | 31.707681 | 0.458243 | 10.604562 | 2.491097 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 8.940240 | -0.858645 | -2.482219 | -1.112090 | -0.579565 | 0.975822 | 2.711670 | 1.641482 | 8.940240 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | ee Temporal Discontinuties | 3.478663 | 0.027675 | -0.949881 | 1.443644 | -1.138712 | 2.306900 | 0.513733 | 3.478663 | -0.081432 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 10.286625 | -1.440522 | -1.525487 | -0.869157 | -1.138520 | -0.591093 | 6.976892 | 3.870383 | 10.286625 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 13.544735 | -1.021965 | -2.043486 | -0.396546 | 0.060251 | 1.808906 | 0.012244 | 13.544735 | 5.855955 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | ee Temporal Discontinuties | 3.772003 | -1.414414 | -0.486147 | 0.095460 | 0.030110 | 3.153513 | -0.717554 | 1.383776 | 3.772003 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | ee Temporal Discontinuties | 5.398538 | -1.185920 | -1.835654 | -0.457376 | -0.462858 | -0.093478 | 1.377368 | 5.398538 | 3.911519 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 10.484137 | -1.297624 | -1.014022 | -0.945261 | -0.727914 | 3.629647 | -0.660514 | 10.484137 | 3.400309 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Variability | 3.059760 | -1.421956 | -0.735770 | -0.666619 | -0.682362 | 3.059760 | 0.464054 | 2.411647 | 2.228934 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 5.165810 | -0.245006 | -1.463384 | -0.720938 | -0.957327 | 2.041318 | 3.593913 | 5.105871 | 5.165810 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 13.993654 | -1.697189 | -0.967149 | -1.002644 | -0.696849 | 6.328372 | -0.765968 | 13.993654 | 7.235540 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | ee Temporal Discontinuties | 4.916300 | -0.947257 | -1.554103 | -0.290975 | 0.106237 | -0.137241 | 1.557493 | 4.916300 | 2.098078 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 3.636340 | -2.077737 | -0.901646 | -0.331214 | -0.063161 | 2.303752 | 0.219371 | 3.636340 | 2.202750 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 7.871715 | -1.353949 | -1.659899 | 0.019094 | -0.771066 | 1.053488 | 2.979745 | 5.655166 | 7.871715 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 4.368111 | 0.064489 | -0.373467 | -0.078779 | -0.703689 | -0.762008 | 1.172883 | 1.209582 | 4.368111 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 8.233591 | -0.739282 | -0.440170 | -1.204784 | -0.621665 | 3.449304 | -0.407642 | 8.233591 | 6.009291 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 8.468923 | -0.206881 | -0.236784 | -1.052641 | -0.647617 | 2.021268 | -0.517516 | 8.468923 | 4.128146 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 94 | N10 | digital_ok | nn Temporal Discontinuties | 7.443236 | -2.629263 | -1.187967 | -0.710578 | -0.303594 | 3.891385 | 2.079480 | 7.443236 | 2.975274 |